You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
How can I label a customized dataset to be able to use in Caffe_segnet?
Which tool or program I should use to create my own label dataset with the same format as dataset used in this tutorial: 'http://mi.eng.cam.ac.uk/projects/segnet/tutorial.html'.
I found that it is Gray images had been created to train the model (trainannot), furthermore, the Softmax layer is created by class_weighting parameters for each class, which should represent the label in this folder trainannot.
My question is, how can i label my own dataset to train the bixel-wise classification ?
How can I label a customized dataset to be able to use in Caffe_segnet?
Which tool or program I should use to create my own label dataset with the same format as dataset used in this tutorial: 'http://mi.eng.cam.ac.uk/projects/segnet/tutorial.html'.
I found that it is Gray images had been created to train the model (trainannot), furthermore, the Softmax layer is created by class_weighting parameters for each class, which should represent the label in this folder trainannot.
My question is, how can i label my own dataset to train the bixel-wise classification ?
softmax layer in this file 'segnet_train.prototxt'
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "conv1_1_D"
bottom: "label"
top: "loss"
softmax_param {engine: CAFFE}
loss_param: {
weight_by_label_freqs: true
ignore_label: 11
class_weighting: 0.2595
class_weighting: 0.1826
class_weighting: 4.5640
class_weighting: 0.1417
class_weighting: 0.9051
class_weighting: 0.3826
class_weighting: 9.6446
class_weighting: 1.8418
class_weighting: 0.6823
class_weighting: 6.2478
class_weighting: 7.3614
}
}
The text was updated successfully, but these errors were encountered: